kin-zhang / nways_accelerated_programming Goto Github PK

Description: The N-Ways to GPU Programming Bootcamp covers the basics of GPU programming and provides an overview of different methods for porting scientific application to GPUs using NVIDIA® CUDA®, OpenACC, standard languages, OpenMP offloading, and/or CuPy and Numba. Throughout the bootcamp, attendees with learn how to analyze GPU-enabled applications using NVIDIA Nsight™ Systems and participate in hands-on activities to apply these learned skills to real-world problems.

• This material originates from the OpenHackathons Github repository. Check out additional materials here.
• NVIDIA HPC SDK
• NVIDIA Nsight™ Systems

1. Clone the repository:

   git clone [email protected]:Kin-Zhang/nways_accelerated_programming.git

2. Build or pull the Docker container:

   docker build -t zhangkin/nways .

3. Run the Docker container:

    docker run --rm -it --runtime nvidia -p 8888:8888 zhangkin/nways
    # if above is not working, try the following
    docker run --gpus all --rm -it -p 8888:8888 zhangkin/nways

4. Open the Jupyter Notebook in your browser (your local host):

   http://localhost:8888
   

5. Follow the instructions in the Jupyter Notebook to proceed with the bootcamp. Link here is to clone code, visualize as jupyter notebook path.
   • labs/_start_nways.ipynb.
   • challenge/minicfd.ipynb.

Demo:

Bootcamp prerequisites: Basic experience with C/C++ or Fortran is needed for the "N-Ways to GPU Programming-C-Fortran" Bootcamp and Python is needed for the "N-Ways to GPU Programming-Python" Bootcamp. No GPU programming experience is required.

Material | PPT, Recording | Video

Day1 – 3 April 2024

• 09:00–09:05 Welcome (Moderator)
• 09:05–09:30 Introduction to GPU Computing (Lecture)
• 09:30–10:00 Introduction to Nsight Systems (Lecture and Read-Only Lab)
• 10:00–11:00 Accelerating Standard C++ and Fortran with GPUs (Lecture and Lab)
• 11:00–11:30 Wrap Up and Q&A

Day2 – 4 April 2024

• 09:00–10:30 Directive Based Programming with OpenACC or OpenMP on GPU (Lecture and Lab)
• 10:30–12:30 CUDA C/Fortran Programming (Lecture and Lab)
• 12:30–12:45 Description of Code Challenge
• 12:45–13:00 Wrap Up and Q&A

Day3 – 5 April 2024

• 09:00–12:00 Code Challenge
• 09:00–0930 Targeting GPUs from Python [Optional]
• 12:00–12:30 Q&A about Code Challenge
• 12:30–13:00 Project Discussion [Optional]